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Antonov, A.V. ; Dietmann, S. ; Wong, P. ; Mewes, H.-W.

TICL - a web tool for network-based interpretation of compound lists inferred by high-throughput metabolomics.

FEBS J. 276, 2084-2094 (2009)
DOI PMC
Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
High-throughput metabolomics is a dynamically developing technology that enables the mass separation of complex mixtures at very high resolution. Metabolic profiling has begun to be widely used in clinical research to study the molecular mechanisms of complex cell disorders. Similar to transcriptomics, which is capable of detecting genes at differential states, metabolomics is able to deliver a list of compounds differentially present between explored cell physiological conditions. The bioinformatics challenge lies in a statistically valid interpretation of the functional context for identified sets of metabolites. Here, we present TICL, a web tool for the automatic interpretation of lists of compounds. The major advance of TICL is that it not only provides a model of possible compound transformations related to the input list, but also implements a robust statistical framework to estimate the significance of the inferred model. The TICL web tool is freely accessible at http://mips.helmholtz-muenchen.de.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter bioinformatics tools for high-throughput metabolomics; metabolomics; statistical analysis and data mining; statistical and bioinformatics tools; web tools for metabolomics; gene-expression; mass-spectrometry; complex functionality; level analysis; pathways; bioinformatics; visualization; patterns; systems; routes
Sprache englisch
Veröffentlichungsjahr 2009
HGF-Berichtsjahr 2009
ISSN (print) / ISBN 1742-464X
e-ISSN 1742-4658
Zeitschrift FEBS Journal, The
Quellenangaben Band: 276, Heft: 7, Seiten: 2084-2094 Artikelnummer: , Supplement: ,
Verlag Wiley
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Bioinformatics and Systems Biology (IBIS)
POF Topic(s) 30505 - New Technologies for Biomedical Discoveries
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-503700-001
PubMed ID 19292876
DOI 10.1111/j.1742-4658.2009.06943.x
Scopus ID 62149124281
Erfassungsdatum 2009-12-31
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